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Image Processing for HTS SQUID probe microscope Advanced Image Processing Seminar Colin Bothwell 0570063.

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Presentation on theme: "Image Processing for HTS SQUID probe microscope Advanced Image Processing Seminar Colin Bothwell 0570063."— Presentation transcript:

1 Image Processing for HTS SQUID probe microscope Advanced Image Processing Seminar Colin Bothwell 0570063

2 General Discussion of Paper Use High Temp SQUID probe microscope Probe allows high spatial resolution of measurement of samples even at room temp Aim to produce magnetic field images Improve images using Image Processing

3 Theory of SQUIDs Superconducting QUantum Interference Device Measure tiny magnetic fields (threshold is around 10 -14 T where 1T=10000Gauss. ) Magnetic field of heart=10 -10 T

4 Theory of SQUIDs To understand SQUIDs need to know basic principles Superconductivity- no resistance Josephson Effect- current flow carried by cooper pairs

5 Theory of SQUIDs Josephson Junction- a junction of 2 S/C materials divided by non-S/C material (oxide) With these principles, SQUID was designed

6 Theory of SQUIDs SQUID has two Josephson Junctions Apply current to SQUID Voltage will oscillate Oscillations depend on magnetic flux

7 Experimental Set-Up Developed HTS SQUID probe microscope using fine permalloy needle as flux guide Images the magnetic field by means of raster scan

8 Experimental Set-up Separation of probe and SQUID adjusted by viewing through glass window PC used to control SQUID

9 Magnetic Image-Deficiencies Resultant images are noisy and unclear because of Background Noise Drifting Data Jumping So…

10 Image Processing! Background Noise  Use image processing algorithm  Calculate mean and standard deviation of power spectrum  Threshold value=P m + αP s  Apply this to each scan line in same way

11 Drift between Lines Drift of flux bias point of SQUID Treated with another algorithm  Drift calculated as difference in the mean value of magnetic field for each scan line

12 Data Jumping Artifacts due to a jump in the flux bias point in SQUID by flux trapping or unexpected noise Jump causes change dynamic range of magnetic field to become larger

13 Data Jumping Small changes can no longer be detected IP detects line with jump by derivation of line data (higher derivation considered to contain jump) so is interpolated with neighbouring lines

14 Conclusion Used high-permeability needle to enable high spatial resolution measurement of samples. Developed IP algorithms for magnetic field data obtained from SQUID probe microscope. Algorithms can remove problems of background noise, drifting and jump data.


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